msdhina

Non zero mean scaling - Not working

6

I've used "lambda x: jnp.mean(x[x > 0])" in place of "jnp.mean" `media_scaler = preprocessing.CustomScaler(divide_operation=lambda x: jnp.mean(x[x > 0])) ` It throws "NonConcreteBooleanIndexError: Array boolean indices must be concrete; got ShapedArray(bool[82])"...

Contribution of Control variables (a.k.a Extra features)

2

How to get contribution for the extra features that is fed into the model?